solution

solution.R

```{r, eval=FALSE, include=FALSE}
library(Ecdat)
library(dplyr)

data("LaborSupply")

# Compute the average annual hours worked by year (plus standard deviation)

LaborSupply %>%
  group_by(year) %>%
  summarise(mean(lnhr), sd(lnhr))

# What age group worked the most hours in the year 1982?

LaborSupply %>%
  filter(year == 1982) %>%
  group_by(age) %>%
  mutate(total_lnhr_age = sum(lnhr)) %>%
  ungroup() %>%
  filter(total_lnhr_age == max(total_lnhr_age))

# Create a variable, `n_years` that equals the number of years an
# individual stays in the panel. Is the panel balanced?

LaborSupply %>%
  group_by(id) %>%
  mutate(n_years = n()) %>%
  ungroup() %>%
  summarise(mean(n_years))

# Which are the individuals that do not have any kids during the whole period?
# Create a variable, `no_kids`, that flags these individuals (1 = no kids, 0 = kids)

LaborSupply = LaborSupply %>%
  group_by(id) %>%
  mutate(n_kids = max(kids)) %>%
  mutate(no_kids = ifelse(n_kids == 0, 1, 0))

# Using the `no_kids` variable from before compute the average wage in 1980 for these two groups (no kids group vs kids group).
LaborSupply %>%
  filter(year == 1980) %>%
  group_by(no_kids) %>%
  summarise(mean(lnwg), sd(lnwg), n())

```